Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
Model transformation means converting an input model available at the beginning of the transformation process to an output model. A widely used approach to model transformation us...
In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...
Abstract: Reuse of software entities such as components or Web services raise composition issues since, most of the time, they present mismatches in their interfaces. These mismatc...
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...